We consider the problem of extracting a complete set of numerical parameters that characterize the robot dynamics, starting from the identified values of dynamic coefficients that linearly parametrize the robot dynamic equations. This information is relevant when realistic dynamic simulations have to be performed using standard packages, or when addressing the efficient numerical implementation of model-based control laws using recursive Newton-Euler algorithms. The formulated problem is highly nonlinear and is solved through the use of global optimization techniques, while imposing also physical bounds on the dynamic parameters. The identification and parameter extraction process is illustrated and experimentally validated on the link dynamics of a KUKA LWR IV+ robot.
2016, 2016 IEEE International Conference on Robotics and Automation (ICRA), Pages 2075-2081
Extracting feasible robot parameters from dynamic coefficients using nonlinear optimization methods (04b Atto di convegno in volume)
Gaz CLAUDIO ROBERTO, Flacco Fabrizio, DE LUCA Alessandro
Gruppo di ricerca: Robotics